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https://github.com/meta-llama/llama-stack.git
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30b2e6a495
# What does this PR do? previously, developers who ran `./scripts/unit-tests.sh` would get `asyncio-mode=auto`, which meant `@pytest.mark.asyncio` and `@pytest_asyncio.fixture` were redundent. developers who ran `pytest` directly would get pytest's default (strict mode), would run into errors leading them to add `@pytest.mark.asyncio` / `@pytest_asyncio.fixture` to their code. with this change - - `asyncio_mode=auto` is included in `pyproject.toml` making behavior consistent for all invocations of pytest - removes all redundant `@pytest_asyncio.fixture` and `@pytest.mark.asyncio` - for good measure, requires `pytest>=8.4` and `pytest-asyncio>=1.0` ## Test Plan - `./scripts/unit-tests.sh` - `uv run pytest tests/unit`
110 lines
4 KiB
Python
110 lines
4 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from llama_stack.apis.common.content_types import TextContentItem
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from llama_stack.apis.inference import (
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CompletionMessage,
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OpenAIAssistantMessageParam,
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OpenAIChatCompletionContentPartTextParam,
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OpenAISystemMessageParam,
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OpenAIUserMessageParam,
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SystemMessage,
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UserMessage,
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)
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from llama_stack.models.llama.datatypes import BuiltinTool, StopReason, ToolCall
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from llama_stack.providers.utils.inference.openai_compat import (
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convert_message_to_openai_dict,
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openai_messages_to_messages,
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)
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async def test_convert_message_to_openai_dict():
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message = UserMessage(content=[TextContentItem(text="Hello, world!")], role="user")
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assert await convert_message_to_openai_dict(message) == {
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"role": "user",
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"content": [{"type": "text", "text": "Hello, world!"}],
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}
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# Test convert_message_to_openai_dict with a tool call
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async def test_convert_message_to_openai_dict_with_tool_call():
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message = CompletionMessage(
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content="",
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tool_calls=[
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ToolCall(call_id="123", tool_name="test_tool", arguments_json='{"foo": "bar"}', arguments={"foo": "bar"})
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],
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stop_reason=StopReason.end_of_turn,
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)
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openai_dict = await convert_message_to_openai_dict(message)
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assert openai_dict == {
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"role": "assistant",
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"content": [{"type": "text", "text": ""}],
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"tool_calls": [
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{"id": "123", "type": "function", "function": {"name": "test_tool", "arguments": '{"foo": "bar"}'}}
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],
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}
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async def test_convert_message_to_openai_dict_with_builtin_tool_call():
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message = CompletionMessage(
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content="",
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tool_calls=[
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ToolCall(
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call_id="123",
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tool_name=BuiltinTool.brave_search,
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arguments_json='{"foo": "bar"}',
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arguments={"foo": "bar"},
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)
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],
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stop_reason=StopReason.end_of_turn,
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)
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openai_dict = await convert_message_to_openai_dict(message)
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assert openai_dict == {
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"role": "assistant",
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"content": [{"type": "text", "text": ""}],
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"tool_calls": [
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{"id": "123", "type": "function", "function": {"name": "brave_search", "arguments": '{"foo": "bar"}'}}
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],
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}
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async def test_openai_messages_to_messages_with_content_str():
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openai_messages = [
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OpenAISystemMessageParam(content="system message"),
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OpenAIUserMessageParam(content="user message"),
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OpenAIAssistantMessageParam(content="assistant message"),
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]
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llama_messages = openai_messages_to_messages(openai_messages)
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assert len(llama_messages) == 3
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assert isinstance(llama_messages[0], SystemMessage)
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assert isinstance(llama_messages[1], UserMessage)
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assert isinstance(llama_messages[2], CompletionMessage)
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assert llama_messages[0].content == "system message"
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assert llama_messages[1].content == "user message"
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assert llama_messages[2].content == "assistant message"
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async def test_openai_messages_to_messages_with_content_list():
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openai_messages = [
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OpenAISystemMessageParam(content=[OpenAIChatCompletionContentPartTextParam(text="system message")]),
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OpenAIUserMessageParam(content=[OpenAIChatCompletionContentPartTextParam(text="user message")]),
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OpenAIAssistantMessageParam(content=[OpenAIChatCompletionContentPartTextParam(text="assistant message")]),
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]
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llama_messages = openai_messages_to_messages(openai_messages)
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assert len(llama_messages) == 3
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assert isinstance(llama_messages[0], SystemMessage)
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assert isinstance(llama_messages[1], UserMessage)
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assert isinstance(llama_messages[2], CompletionMessage)
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assert llama_messages[0].content[0].text == "system message"
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assert llama_messages[1].content[0].text == "user message"
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assert llama_messages[2].content[0].text == "assistant message"
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